TGF-beta reduces DNA ds-break repair mechanisms to heighten genetic diversity and adaptability of CD44+/CD24- cancer cells

Many lines of evidence have indicated that both genetic and non-genetic determinants can contribute to intra-tumor heterogeneity and influence cancer outcomes. Among the best described sub-population of cancer cells generated by non-genetic mechanisms are cells characterized by a CD44+/CD24- cell surface marker profile. Here, we report that human CD44+/CD24- cancer cells are genetically highly unstable due to intrinsic defects in their DNA repair capabilities. In fact, in CD44+/CD24- cells constitutive activation of the TGF-beta axis was both necessary and sufficient to reduce the expression of genes that are critical in coordinating DNA damage repair mechanisms. Consequently, we observed that cancer cells that reside in a CD44+/CD24- state are characterized by increased accumulation of DNA copy number alterations, greater genetic diversity and improved adaptability to drug treatment. Together, these data suggest that the transition into a CD44+/CD24- cell state can promote intra-tumor genetic heterogeneity, spur tumor evolution and increase tumor fitness

Unresolved endoplasmic reticulum stress engenders immune-resistant, latent pancreatic cancer metastases

The majority of patients with pancreatic ductal adenocarcinoma (PDA) develop metastatic disease after resection of their primary tumor. We found that livers from patients and mice with PDA harbor single, disseminated cancer cells (DCCs) lacking expression of cytokeratin-19 (CK19) and major histocompatibility complex class I (MHCI). We created a mouse model to determine how these DCCs develop. Intra-portal injection of immunogenic PDA cells into pre-immunized mice seeded livers only with single, non-replicating DCCs that were CK19(-) and MHCI(-) The DCCs exhibited an endoplasmic reticulum (ER) stress response but, paradoxically lacked both inositol-requiring enzyme 1alpha activation and expression of the spliced form of transcription factor XBP1 (XBP1s). Inducible expression of XBP1s in DCCs, in combination with T cell-depletion, stimulated the outgrowth of macro-metastatic lesions that expressed CK19 and MHCI. Thus, unresolved ER stress enables DCCs to escape immunity and establish latent metastases

A Molecular Clock Infers Heterogeneous Tissue Age Among Patients with Barrett's Esophagus

National Institutes of Health (www.nih.gov) and the National Cancer Institute (www.cancer.gov) under grants U01CA182940 (BG-U01) (to EGL, CJW, WDH, WMG, and KC), 5P30CA015704 (to WMG and CJW), 5U01CA152756 (to WMG and CJW), 5U54CA163060 (to AC), and NIH1P50CA150964-01A1 (to JEW

Single-Cell Applications of Next-Generation Sequencing

The single cell is considered the basic unit of biology, and the pursuit of understanding how heterogeneous populations of cells can functionally coexist in tissues, organisms, microbial ecosystems, and even cancer, makes them the subject of intense study. Next-generation sequencing (NGS) of RNA and DNA has opened a new frontier of (single)-cell biology. Hundreds to millions of cells now can be assayed in parallel, providing the molecular profile of each cell in its milieu inexpensively and in a manner that can be analyzed mathematically. The goal of this article is to provide a high-level overview of single-cell sequencing for the nonexpert and show how its applications are influencing both basic and applied clinical studies in embryology, developmental genetics, and cancer

Single-cell RNA-seq analysis identifies markers of resistance to targeted BRAF inhibitors in melanoma cell populations

Single-cell RNA-seq's (scRNA-seq) unprecedented cellular resolution at a genome wide scale enables us to address questions about cellular heterogeneity that are inaccessible using methods that average over bulk tissue extracts. However, scRNA-seq datasets also present additional challenges such as high transcript dropout rates, stochastic transcription events, and complex population substructures. Here, we present SAKE (Single-cell RNA-seq Analysis and Klustering Evaluation): a robust method for scRNA-seq analysis that provides quantitative statistical metrics at each step of the scRNA-seq analysis pipeline. Comparing SAKE to multiple single-cell analysis methods shows that most methods perform similarly across a wide range cellular contexts, with SAKE outperforming these methods in the case of large complex populations. We next applied the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors. Single-cell RNA-seq data from both the Fluidigm C1 and 10x Genomics platforms were analyzed with SAKE to dissect this problem at multiple scales. Data from both platforms indicate that BRAF inhibitor resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance. These experimentally validated markers of BRAFi resistance share overlap with previous analysis in different melanoma cell lines, demonstrating the generality of these findings and highlighting the utility of single-cell analysis to elucidate mechanisms of BRAFi resistance

Evolution of Barrett's esophagus through space and time at single-crypt and whole-biopsy levels

This work was primarily supported by National Cancer Institute grants R01 CA140657 and P01 CA091955 (T.G.P., X.L., C.A.S., B.J.R., M.K.K., and C.C.M.). This work was also supported in part by NIH grants R01 CA149566, R01 CA170595, and R01 CA185138, as well as CDMRP Breast Cancer Research Program Award BC132057. T.A. G. was supported by Cancer Research UK (A19771).